From Vibe Coding's Intoxication to VISE's Disciplined Power
IN A SPARSE office in San Francisco's Mission District, a developer named Sarah stares at her screen in horror. Three months ago, she'd been the office hero—shipping features at superhuman speed using Andrej Karpathy's "vibe coding" method. Just speak to the AI, accept its suggestions, never look back. Today, she faces a codebase that no human understands: 1,400 lines in a single file, inconsistent naming conventions, odd comments scattered throughout. The bug reports multiply faster than she can comprehend the code that spawned them. This isn't just technical debt—it's technical bankruptcy.
Sarah's crisis represents a crossroads facing every developer in 2025. When Karpathy, former Tesla AI director and OpenAI co-founder, posted about his new coding approach in February 2025, the industry gasped. "There's a new kind of coding I call 'vibe coding'," he wrote, "where you fully give in to the vibes, embrace exponentials, and forget that the code even exists." Using Cursor Composer with Anthropic's Sonnet and voice input via SuperWhisper, he barely touched the keyboard. Within weeks, vibe coding became Silicon Valley's latest gospel. The promise was intoxicating—10x productivity, democratized programming, the end of syntax errors.
What makes this particularly urgent is the speed of divergence. While some developers embrace vibe coding's chaos, others discover a disciplined alternative. David Farago, a deep learning engineer watching the madness unfold, coined "VISE coding"—vibe plus Software Engineering—in a LinkedIn post. The name evokes a craftsman's vise, holding work steady for precise manipulation. As Farago explains, "Vibe coding is neither maintainable nor sustainable, since technical debt accumulates rapidly." Early adopters report something remarkable: they code even faster than pure vibers, but their code remains comprehensible, secure, maintainable.
For the software industry, this isn't merely a methodological debate. It's an existential choice. The tools that define the next decade of development are being shaped now. The patterns being established will determine whether AI amplifies engineering excellence or accelerates technical chaos. As one CTO told me, "We're watching two parallel universes emerge. In one, AI makes everyone a coder. In the other, AI makes coders superhuman. The difference is discipline."
The Vibe Coding Trap
The promise of AI coding initially seemed irresistible. Developers reported 10x productivity gains. Non-programmers built applications without learning syntax. The democratization narrative was powerful: anyone could code now, barriers had fallen.
But the reality proved sobering. IBM's analysis found that "code generated using AI is often excluded from code reviews and security checks." Studies show 36% to 48% of AI-generated code contains security vulnerabilities. In March 2025, a vibe-coded payment gateway approved $2 million in fraudulent transactions due to inadequate input validation—vulnerabilities that human review would have caught.
The pattern became clear: vibe coding optimizes for initial velocity while ignoring terminal velocity. As one developer discovered after building a game in an afternoon: "the code is a mess... everything in one 1,400-line file with inconsistent naming and odd comments." The time saved upfront evaporates in debugging, security fixes, and eventual rewrites.
Enter VISE: The Discipline That Accelerates
VISE coding emerged as the answer—not abandoning AI's power, but channeling it through engineering discipline. David Farago, who coined the term, explained that "Vibe coding is neither maintainable nor sustainable, since technical debt accumulates rapidly." VISE adds the structure needed for production software.
The core insight is counterintuitive: discipline accelerates development rather than constraining it. When AI writes tests alongside code, bugs surface immediately. When AI documents every function, onboarding accelerates. When AI follows strict standards, refactoring becomes trivial.
Singapore's GovTech validated this approach on a critical national platform. Using VISE principles—mandatory tests, documentation, and security scanning for all AI-generated code—they shipped 60% faster than traditional development while achieving 90% code coverage and zero critical vulnerabilities.
Modern tools now support VISE workflows. Cursor IDE's "AI Rules" feature enforces constraints—the AI literally cannot generate code violating specified standards. GitHub Copilot's "test-first" mode ensures comprehensive testing. The tooling ecosystem is evolving to make disciplined AI coding the default, not the exception.
VISE in Practice: The Implementation Guide
Successful VISE implementation follows clear patterns that any team can adopt:
Test-Augmented Development
Every AI interaction must include tests. Instead of "Write a function to validate email addresses," prompt: "Write tests for an email validation function," then "Now implement the function to pass these tests." This test-first approach forces clarity about requirements and catches issues immediately.
Small, Reviewable Changes
VISE mandates incremental development. Break requests into digestible chunks: "Create a User model with basic fields." Review. "Add password hashing." Review. "Create a registration endpoint." Review. Each step remains comprehensible and reversible.
Living Documentation
After generating any function, immediately request: "Write comprehensive documentation including parameters, return values, edge cases, and usage examples." The AI excels at this tedious but crucial work. Future modifications become trivial when every decision is documented.
Security Integration
Configure IDEs to scan AI-generated code immediately. When vulnerabilities surface, educate the AI: "The security scanner found SQL injection risk. Rewrite using parameterized queries." This creates a feedback loop, improving future generations.
Human-AI Workflow
The most successful teams clearly define roles: Humans architect, AI implements, humans review, AI tests, humans verify, AI documents, humans approve. This division leverages each participant's strengths while maintaining control.
VISE at Glass Umbrella: Building The Smithy
At Glass Umbrella, we're not just advocating for VISE—we're living it. Our flagship project, The Smithy (an educational RPG for tweens), demonstrates how VISE principles scale to ambitious creative projects.
Our implementation starts with comprehensive knowledge repositories. Every game system, from our music-magic mechanics to our trust-based NPC relationships, has detailed documentation that guides our AI assistants. When we ask Claude Code to implement a new feature, it references our design documents, coding standards, and architectural decisions.
We've created specialized AI agents for different aspects of development. Our "game mechanics reviewer" ensures every feature aligns with our core design pillars. Our "narrative consistency checker" validates that code changes don't break story logic. Our "educational impact assessor" confirms that gameplay elements support learning objectives.
The results speak for themselves. Despite being a small team, we're building systems that would typically require dozens of developers. Our room schema (v2.0) powers dynamic environments with conditional descriptions, NPC schedules, and quest integration—all implemented through VISE-guided AI assistance. Our experience system, inspired by DragonRealms' skill-based progression, was prototyped in days rather than months.
Most importantly, VISE allows us to maintain our values while moving fast. Every line of code is reviewed for alignment with our mission of trust-building and sovereignty. Our AI assistants don't just write code—they help us ensure that code embodies our principles of transparency, player agency, and educational impact.
The Craftsman's Path: A Personal VISE Journey
My own path to VISE began with recognizing AI's power while respecting code's complexity. Starting with "The Self-Taught Programmer" and the Odin Project's foundations, I built a knowledge repository that became my north star for AI-assisted development.
This repository evolved into something more: when Claude Code enabled agent creation, I built a pair programmer that reviews my code against these accumulated insights. The vise metaphor resonates deeply—in woodworking, a vise enables precision by holding work steady. My AI pair programmer provides that same stability, ensuring every line of code meets established standards while moving at AI speed.
My workflow alternates between innovation sprints and technical debt payment. This rhythm acknowledges that code is never complete. During innovation sprints, AI helps explore new possibilities rapidly. During debt payment sprints, AI assists in refactoring, documenting, and strengthening the foundation. The result? I'm not just shipping faster—I'm shipping better.
The VISE Revolution: Why Discipline Wins
VISE represents software engineering's next evolutionary leap. The core insight: AI amplifies whatever process you feed it. Feed it chaos, get faster chaos. Feed it discipline, get faster discipline.
This isn't about constraining AI—it's about unleashing its full potential. An AI that writes tests is exponentially more powerful than one that just writes code. An AI working within architectural guidelines produces better results than one running wild. When every developer has an AI assistant that follows best practices, the entire industry's baseline rises.
The democratization promise of AI coding achieves reality through VISE, not vibe. Junior developers get superhuman assistance that follows senior-level practices. Open source projects become more accessible when AI can explain any codebase while maintaining standards. Small teams like ours at Glass Umbrella can build ambitious projects that would have required massive resources just years ago.
We're not choosing between human and AI coding. We're combining them in ways that amplify both. The vise doesn't limit—it enables precision at speed.
The Path Forward: Making VISE Your Reality
The age of AI-assisted coding has arrived. The question isn't whether to use AI—it's how to use it wisely. VISE provides that path.
For Individual Developers:
Start with one VISE principle in your next coding session. Add tests to every AI-generated function. Review before accepting. Document as you go. Build your own knowledge repository. Create AI agents that enforce your standards. Feel the difference between mere speed and sustainable velocity.
For Teams:
Establish AI coding guidelines today. Create .ai-rules files that encode your standards. Set up automated scanning pipelines. Define clear human-AI workflows. Share successful patterns. The teams mastering VISE collaboration will define the next decade of software development.
For Organizations:
Invest in VISE-compatible tooling and training. Don't just teach prompt engineering—teach AI-assisted software engineering. Create frameworks that embrace AI's power while maintaining quality standards. Look to examples like Glass Umbrella, where small teams achieve ambitious goals through disciplined AI use.
For the Industry:
We need to evolve beyond the vibe coding hype. Share VISE patterns and practices. Build tools that make discipline the default. Celebrate projects that demonstrate sustainable AI-assisted development. The future belongs to those who combine AI's power with engineering wisdom.
At Glass Umbrella, we're proving that VISE isn't just theory—it's the foundation for building meaningful, maintainable software. Whether it's The Smithy's educational gameplay or your next project, the principles remain the same: AI amplifies discipline, discipline enables mastery, and mastery creates lasting value.
The vise metaphor captures it perfectly. Like a craftsman's tool that enables precision work, VISE holds our code steady while we shape it with AI's power. The result isn't just faster development—it's better development.
Choose VISE. Choose mastery. Build software that lasts.
